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extended 006 with metadata example and printf styling
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‎006_Dictionaries.ipynb

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"***"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## A `dict` as a Metadata Container"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"We will now explore the use of a `dict` as a [metadata](https://en.wikipedia.org/wiki/Metadata) container. \n",
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"\n",
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"Descriptive metadata provides a resource for several purposes such as data discovery and identification. Following our previous examples of experiments collecting water salinity and temperature values, we will use a `dict` to store metadata such as:\n",
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"\n",
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"- The author of the measures (`\"first_name\"` and `\"last_name\"`).\n",
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"- The location where the measurements took place (`\"latitude\"` and `\"longitude\"`).\n",
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"- The time frame when the measures happened (`\"start_timestamp\"` and `\"end_timestamp\"`)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Thus, a complete set of metadata will be represented by a `dict` containing the following six keys (with the corresponding value type):\n",
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"\n",
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"- `\"first_name\"` ➜ `str` type\n",
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"- `\"last_name\"` ➜ `str` type\n",
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"- `\"latitude\"` ➜ `float` type\n",
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"- `\"longitude\"` ➜ `float` type\n",
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"- `\"start_timestamp\"` ➜ `datetime` type\n",
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"- `\"end_timestamp\"` ➜ `datetime` type"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This is the first time that we use the [`datetime`](https://docs.python.org/3.6/library/datetime.html?#module-datetime) type! "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<img align=\"left\" width=\"6%\" style=\"padding-right:10px;\" src=\"images/key.png\">\n",
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"\n",
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"A variable of `datetime` type contains all the information from both a date and a time."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"As you can read from the [Python documentation](https://docs.python.org/3.6/library/datetime.html?#datetime-objects), the `datetime` constructor is part of the `datetime` module (yes, they have both the same name!) and takes several parameters: \n",
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"\n",
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"- `datetime(year, month, day, hour=0, minute=0, second=0, microsecond=0, tzinfo=None, *, fold=0)` "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"For the aims of this notebook, you can just ignore all the parameters after the first six. In fact, we will call the `datetime` constructor with only 6 values (from `year` to `second`)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from datetime import datetime\n",
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"\n",
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"begin_timestamp = datetime(2019, 2, 22, 12, 32, 40)\n",
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"print(str(begin_timestamp))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**How can the above code actually work?** It works because the parameters after the first 3 (e.g., `hour=0`) have a **default value** assigned to them (the `=0` in this specific example). This implies that, if you do *not* pass values for those parameters, Python will assign them those defined default values. "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"We can now write our `metadata`:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"metadata = dict()\n",
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"metadata[\"first_name\"] = \"John\"\n",
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"metadata[\"last_name\"] = \"Doe\"\n",
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"metadata[\"latitude\"] = 43.135555\n",
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"metadata[\"longitude\"] = -70.939534\n",
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"metadata[\"start_timestamp\"] = datetime(2019, 2, 22, 12, 32, 40)\n",
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"metadata[\"end_timestamp\"] = datetime(2019, 2, 22, 12, 34, 14)\n",
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"\n",
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"print(metadata)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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" "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"solution2": "hidden",
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"solution2_first": true
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},
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"source": [
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"<img align=\"left\" width=\"6%\" style=\"padding-right:10px;\" src=\"images/test.png\">\n",
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"\n",
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"Populate and print a `metadata` dictionary containing the following three keys: your `\"username\"`, the `\"begin_time\"` and the `\"end_time\"` for the execution of this exercise."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"solution2": "hidden"
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},
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"outputs": [],
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"source": [
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"metadata = dict()\n",
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"metadata[\"username\"] = \"jdoe\"\n",
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"metadata[\"start_timestamp\"] = datetime(2019, 2, 22, 12, 34, 20)\n",
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"metadata[\"end_timestamp\"] = datetime(2019, 2, 22, 12, 34, 21)\n",
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"\n",
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"print(metadata)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"***"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# More on String Formatting"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"In this last section of this notebook, we will explore different mechanisms that Python provides for printing (**string formatting**) a value."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"At this moment, you know how to print a value with `str` type:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 28,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The first name is: John\n"
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]
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}
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],
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"source": [
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"metadata = dict()\n",
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"metadata[\"first_name\"] = \"John\"\n",
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"\n",
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"print(\"The first name is: \" + metadata[\"first_name\"])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You also know that you can type-casting types using `str()`:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 29,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The position is: 43.135555, -70.939534\n",
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"Start time: 2019-02-22 12:32:40\n"
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]
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}
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],
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"source": [
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"metadata = dict()\n",
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"metadata[\"latitude\"] = 43.135555\n",
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"metadata[\"longitude\"] = -70.939534\n",
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"metadata[\"start_timestamp\"] = datetime(2019, 2, 22, 12, 32, 40)\n",
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"\n",
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"print(\"The position is: \" + str(metadata[\"latitude\"]) + \", \" + str(metadata[\"longitude\"]))\n",
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"print(\"Start time: \" + str(metadata[\"start_timestamp\"]))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"It is possible to achieve the same results by using the `%` modulo operator like in the following examples:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 33,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The first name is: John\n"
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]
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}
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],
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"source": [
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"metadata = dict()\n",
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"metadata[\"first_name\"] = \"John\"\n",
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"\n",
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"print(\"The first name is: %s\" % (metadata[\"first_name\"], ))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 37,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The position is: 43.135558, -70.939534\n",
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"Start time: 2019-02-22 12:32:40\n"
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]
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}
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],
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"source": [
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"metadata = dict()\n",
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"metadata[\"latitude\"] = 43.135558\n",
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"metadata[\"longitude\"] = -70.939534\n",
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"metadata[\"start_timestamp\"] = datetime(2019, 2, 22, 12, 32, 40)\n",
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"\n",
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"print(\"The position is: %s, %s\" % (metadata[\"latitude\"], metadata[\"longitude\"]))\n",
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"print(\"Start time: %s\" % (metadata[\"start_timestamp\"], ))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"If you look at the above examples, you will noticed the presence of `%s` as placeholders in the string. The string is followed by a `%` operator, then by one or more variables enclosed in square brackets."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<img align=\"left\" width=\"6%\" style=\"padding-right:10px;\" src=\"images/info.png\">\n",
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"\n",
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"In the above code, the values after the `%` operator that are inside the square brackets create a [`tuple`](https://docs.python.org/3.6/library/stdtypes.html?#tuples). <br>\n",
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"A `tuple` is a Python container that represents an immutable sequence (thus, you cannot change the content of a `tuple`)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"String formatting using the `%` operator provides [additional printing options](https://docs.python.org/3.6/library/stdtypes.html#printf-style-string-formatting). Among them, you can decide how many decimal digits will be printed for a `float` value. \n",
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"\n",
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"For instance, by using `%.4f` as a placeholder, Python will print **only** the first four decimal digits: "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 41,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The position is: 43.1356, -70.9395\n"
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]
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}
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],
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"source": [
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"metadata = dict()\n",
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"metadata[\"latitude\"] = 43.135558\n",
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"metadata[\"longitude\"] = -70.939534\n",
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"\n",
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"print(\"The position is: %.4f, %.4f\" % (metadata[\"latitude\"], metadata[\"longitude\"]))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"***"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"* [The official Python 3.6 documentation](https://docs.python.org/3.6/index.html)\n",
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" * [Glossary](https://docs.python.org/3.6/glossary.html)\n",
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" * [Mapping Types - dict](https://docs.python.org/3.6/library/stdtypes.html#mapping-types-dict)\n",
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" * [Collections - OrderedDict](https://docs.python.org/3.6/library/collections.html?highlight=ordereddict#ordereddict-objects)"
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" * [Collections - OrderedDict](https://docs.python.org/3.6/library/collections.html?highlight=ordereddict#ordereddict-objects)\n",
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" * [`datetime`](https://docs.python.org/3.6/library/datetime.html?#module-datetime) \n",
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" * [`tuple`](https://docs.python.org/3.6/library/stdtypes.html?#tuples)\n",
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"* [Hash function](https://en.wikipedia.org/wiki/Hash_function)\n",
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"* [Metadata](https://en.wikipedia.org/wiki/Metadata)"
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]
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},
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{

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